Files
manual_slop/src/performance_monitor.py
2026-03-08 03:11:11 -04:00

235 lines
6.9 KiB
Python

"""
Performance Monitor - Real-time FPS, frame time, and CPU usage tracking.
This module provides the PerformanceMonitor singleton class for tracking
application performance metrics with efficient O(1) moving averages.
Key Features:
- FPS and frame time tracking with rolling history
- CPU percentage monitoring via background thread
- Per-component timing with start_component() / end_component()
- Efficient moving average using deque + running sum
- Thread-safe metric collection
Usage:
perf = get_monitor()
perf.enabled = True
# In render loop:
perf.start_frame()
perf.start_component('panel_a')
# ... render panel A ...
perf.end_component('panel_a')
perf.end_frame()
# Get metrics:
metrics = perf.get_metrics()
fps = metrics['fps']
avg_frame_time = metrics['frame_time_ms_avg']
Metrics Available:
- fps: Instantaneous frames per second
- fps_avg: Rolling average FPS
- last_frame_time_ms: Last frame duration in milliseconds
- frame_time_ms_avg: Rolling average frame time
- cpu_percent: Current CPU usage
- cpu_percent_avg: Rolling average CPU usage
- input_lag_ms: Input latency estimate
- time_<component>_ms: Per-component timing
- time_<component>_ms_avg: Per-component rolling average
Thread Safety:
- All public methods are thread-safe
- Uses threading.Lock for state mutations
- Background CPU thread polls every 1 second
Configuration:
- history_size: Number of samples for rolling averages (default: 300)
- sample_interval: Minimum time between history samples (default: 100ms)
Integration:
- Instantiated as singleton via get_monitor()
- Used by gui_2.py for Diagnostics Panel
- Exposed via Hook API at /api/performance
"""
from __future__ import annotations
import time
import psutil
import threading
from typing import Any, Optional, Callable, Dict, List
from collections import deque
_instance: Optional[PerformanceMonitor] = None
def get_monitor() -> PerformanceMonitor:
global _instance
if _instance is None:
_instance = PerformanceMonitor()
return _instance
class PerformanceMonitor:
"""
Tracks application performance metrics like FPS, frame time, and CPU usage.
Supports thread-safe tracking for individual components with efficient moving averages.
"""
def __init__(self, history_size: int = 300) -> None:
self.enabled: bool = False
self.history_size = history_size
self._lock = threading.Lock()
self._start_time: Optional[float] = None
self._last_frame_start_time: float = 0.0
self._last_frame_time: float = 0.0
self._fps: float = 0.0
self._last_calculated_fps: float = 0.0
self._frame_count: int = 0
self._fps_timer: float = 0.0
self._cpu_percent: float = 0.0
self._input_lag_ms: float = 0.0
self._component_starts: dict[str, float] = {}
self._component_timings: dict[str, float] = {}
# Rolling history and running sums for O(1) average calculation
# deques are thread-safe for appends and pops.
self._history: Dict[str, deque[float]] = {}
self._history_sums: Dict[str, float] = {}
# For slowing down graph updates
self._last_sample_time = 0.0
self._sample_interval = 0.1 # 100ms
# Thread for CPU monitoring
self._stop_event = threading.Event()
self._cpu_thread = threading.Thread(target=self._monitor_cpu, daemon=True)
self._cpu_thread.start()
def _monitor_cpu(self) -> None:
while not self._stop_event.is_set():
try:
val = psutil.cpu_percent(interval=None)
with self._lock:
self._cpu_percent = val
except Exception:
pass
time.sleep(1.0)
def _add_to_history(self, key: str, value: float) -> None:
"""Thread-safe O(1) history update."""
with self._lock:
if key not in self._history:
self._history[key] = deque(maxlen=self.history_size)
self._history_sums[key] = 0.0
h = self._history[key]
if len(h) == self.history_size:
removed = h[0] # peek left
self._history_sums[key] -= removed
self._history_sums[key] += value
h.append(value)
def _get_avg(self, key: str) -> float:
"""Thread-safe O(1) average retrieval."""
with self._lock:
h = self._history.get(key)
if not h or len(h) == 0:
return 0.0
return self._history_sums[key] / len(h)
def start_frame(self) -> None:
now = time.time()
with self._lock:
if self._last_frame_start_time > 0:
dt = now - self._last_frame_start_time
if dt > 0:
self._fps = 1.0 / dt
self._last_frame_start_time = now
self._start_time = now
self._frame_count += 1
def end_frame(self) -> None:
if self._start_time is None:
return
now = time.time()
elapsed = now - self._start_time
frame_time_ms = elapsed * 1000
with self._lock:
self._last_frame_time = frame_time_ms
cpu = self._cpu_percent
ilag = self._input_lag_ms
fps = self._fps
# Slow down history sampling for core metrics
if now - self._last_sample_time >= self._sample_interval:
self._last_sample_time = now
self._add_to_history('frame_time_ms', frame_time_ms)
self._add_to_history('cpu_percent', cpu)
self._add_to_history('input_lag_ms', ilag)
self._add_to_history('fps', fps)
self._fps_timer += elapsed
if self._fps_timer >= 1.0:
with self._lock:
self._last_calculated_fps = self._frame_count / self._fps_timer
self._frame_count = 0
self._fps_timer = 0.0
def start_component(self, name: str) -> None:
if not self.enabled: return
now = time.time()
with self._lock:
self._component_starts[name] = now
def end_component(self, name: str) -> None:
if not self.enabled: return
now = time.time()
with self._lock:
start = self._component_starts.pop(name, None)
if start is not None:
elapsed = (now - start) * 1000
with self._lock:
self._component_timings[name] = elapsed
self._add_to_history(f'comp_{name}', elapsed)
def get_metrics(self) -> dict[str, float]:
"""Returns current metrics and their moving averages. Thread-safe."""
with self._lock:
fps = self._fps
last_ft = self._last_frame_time
cpu = self._cpu_percent
ilag = self._input_lag_ms
last_calc_fps = self._last_calculated_fps
timings_snapshot = dict(self._component_timings)
metrics = {
'fps': fps,
'fps_avg': self._get_avg('fps'),
'last_frame_time_ms': last_ft,
'frame_time_ms_avg': self._get_avg('frame_time_ms'),
'cpu_percent': cpu,
'cpu_percent_avg': self._get_avg('cpu_percent'),
'input_lag_ms': ilag,
'input_lag_ms_avg': self._get_avg('input_lag_ms')
}
for name, elapsed in timings_snapshot.items():
metrics[f'time_{name}_ms'] = elapsed
metrics[f'time_{name}_ms_avg'] = self._get_avg(f'comp_{name}')
return metrics
def get_history(self, key: str) -> List[float]:
"""Returns a snapshot of the full history buffer for a specific metric key."""
with self._lock:
if key in self._history:
return list(self._history[key])
if f'comp_{key}' in self._history:
return list(self._history[f'comp_{key}'])
return []
def stop(self) -> None:
self._stop_event.set()
if self._cpu_thread.is_alive():
self._cpu_thread.join(timeout=2.0)